Results for “production”

Build production ML systems with PyTorch 2.x, TensorFlow, and modern ML frameworks, including model serving, feature engineering, A/B testing, and monitoring.

Build production-ready AI agents with type-safe tool use, structured outputs, dependency injection, and multi-model support using PydanticAI.

Generate production-quality React + Tailwind CSS code using the Rayden UI component library with correct props, design tokens, and layout patterns.

Design and review Salesforce sandbox topology, refresh cadence, data masking, and environment purpose to keep production data protected and refreshes manageable.

Guides backend development across API design, authentication, databases, performance, security, scalability, and testing, with quick decision guides and defaults for production-ready systems.

Manages the lifecycle of large language models in production, covering model versioning, prompt management, inference optimization, and cost control.

Enforces production-grade REST API design, distributed systems patterns, database design, and event-driven architecture at a principal-engineer level.

Design and implement production-grade GraphQL APIs with schema design, DataLoader for N+1 prevention, Apollo Client caching, and federation patterns.

Provides guidance on production AI operations including RAG pipelines, vector databases, embeddings, fine-tuning, prompt engineering, cost estimation, and quality evaluation.

Production-ready patterns for building LLM applications. Covers RAG pipelines, agent architectures, prompt IDEs, and LLMOps monitoring. Use when designing AI applications, implementing RAG, building agents, or setting up LLM observability.

Build production-ready Web3 applications, smart contracts, and decentralized systems. Implements DeFi protocols, NFT platforms, DAOs, and enterprise blockchain integrations. Use PROACTIVELY for smart contracts, Web3 apps, DeFi protocols, or blockchain infrastructure.

Use this skill for removing accidental complexity, reducing duplication, clarifying boundaries, preserving behavior. Trigger when the task involves programming work related to Code Simplification, production implementation, audits, debugging, strategy, or validation.

Use this skill for dependency upgrades, SDK migrations, breaking changes, compatibility plans, rollback. Trigger when the task involves programming work related to Deprecation Migration, production implementation, audits, debugging, strategy, or validation.

Use this skill for performance, reliability, observability, SLO risk, production diagnostics. Trigger when the task involves agent profile work related to Performance SRE Agent, implementation, audits, debugging, strategy, or validation.

Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.

Open-source AI observability platform for LLM tracing, evaluation, and monitoring. Use when debugging LLM applications with detailed traces, running evaluations on datasets, or monitoring production AI systems with real-time insights.

Design and build production-ready frontend interfaces with design systems, responsive layouts, accessible components, and dark mode support. Use when the user requests frontend design or provides relevant inputs for this workflow.

Deploy trained machine learning models as production-ready services using REST APIs, containers, serverless functions, and orchestration platforms. Use when the user requests model deployment or provides relevant inputs for this workflow.

Expert skill for building LLM applications with LangChain — LCEL chains, RAG pipelines, agent orchestration, LangGraph integration, LangSmith observability, and production deployment via LangServe. Use when working with LangChain or comparing LLM application frameworks.

Expert in LangGraph - the production-grade framework for building stateful, multi-actor AI applications. Covers graph construction, state management, cycles and branches, persistence with checkpointers, human-in-the-loop patterns, and the ReAct agent pattern. Used in production at LinkedIn, Uber, and 400+ companies. This is LangChain's recommended approach for building agents. Use when "langgraph, langchain agent, stateful agent, agent graph, react agent, agent workflow, multi-step agent, langgraph, langchain, agents, state-machine, workflow, graph, ai-agents, orchestration" mentioned.

Manage production secret infrastructure with HashiCorp Vault, cloud secret stores, automated rotation, and audit logging.

Build real-time streaming applications with the Azure Event Hubs SDK for Java, including sending and receiving events, batch processing, and production-ready event processors.

Turn model work into a production ML system with data contracts, repeatable training, measurable quality gates, deployable artifacts, and operational monitoring.

Provides production-grade Laravel architecture patterns for building scalable, maintainable applications with controllers, services, Eloquent ORM, queues, events, caching, and API resources.

Provides deployment strategies, CI/CD pipeline patterns, Docker containerization best practices, health checks, and production readiness guidance for web applications.

Provides expert guidance on modern Julia 1.10+ development, covering performance optimization, multiple dispatch, tooling, testing, and production-ready practices.

Build production-grade stateful AI agents using LangGraph, covering graph construction, state management, persistence, and human-in-the-loop patterns.

Builds production-ready frontend pages with premium UI design, cinematic animations, AI-generated media assets, persuasive copywriting, and generative art.

Create explainer videos from script to final cut using AI tools for voiceover, visuals, and assembly.

Provides opinionated defaults and reference documentation for building production TypeScript applications with Effect v4, covering schemas, services, layers, configuration, scheduling, caching, streams, HTTP clients, and testing.

Builds production-grade web or mobile interfaces with distinctive design, modern CSS, and purposeful motion, inferring intent from the codebase without asking questions.

Provides a frontend design mode for strong visual direction, UI polish, redesigns, landing pages, and production-grade interface work, including shadcn-based surfaces.

Provides expert-level guidance for Rust 1.75+ development, covering async programming, advanced type system features, performance optimization, and production-ready systems programming.

Turn model work into a production ML system with data contracts, reproducible training, quality gates, deployable artifacts, and monitoring.

Operates Laravel applications in production, covering Horizon, queues, scheduler, Octane, Redis, Supervisor, PHP-FPM, cache, and deployment with safety gates for destructive commands.

Verifies that tests for already-implemented behavior are meaningful by temporarily breaking the production code and confirming the test fails for the expected reason.